Attacking just two hub nodes in the construction schedule risk network of a pumped storage power station can almost completely disable the entire construction process network, according to a simulation study published in Discover Applied Sciences. While the modeled system withstands random operational disturbances without widespread collapse, it displays acute vulnerability when intentional disruptions strike key supervision nodes.
The investigation focused on pumped storage power stations, where complex construction schedules require managing both the direct interrelation among diverse risk factors and their cross-coupling with physical construction activities. To capture these complex spatiotemporal interactions systematically, the research team performed a spatiotemporal complexity analysis of project operations. Using this analytical foundation, the authors constructed a bilayer coupling network that explicitly separated the system into two interacting layers: a risk layer comprising 18 risk nodes and an operational layer comprising 23 construction process nodes.
To analyze how disturbances interact across the dual network layers, the authors integrated two analytical modeling techniques. First, the researchers applied the Gray DEMATEL method to identify and map the underlying causal relationships operating among the 18 schedule risk factors. Second, the team formulated a coupling matrix to quantify the disturbance effects that these risk factors exert directly on individual construction processes. This dual framework allowed the investigators to represent both the internal spread of risks among themselves and the cross-network transmission of delays into ongoing construction tasks.
Building upon this structural foundation, the authors established two complementary propagation models alongside a three-part evaluation framework. For the risk layer, the researchers designed a cascading failure model to simulate how an initial disruption propagates through interconnected vulnerabilities. For the process layer, they formulated a delay propagation model to trace the resulting schedule delays across dependent tasks. To measure overall system performance under varying operational conditions, the authors evaluated three core robustness indicators: node functional robustness, schedule robustness, and collaborative efficiency across the modeled network.
The researchers tested their framework through an empirical case study of a pumped storage power station project, simulating system responses under multiple experimental scenarios. These computational scenarios included single-risk disturbances, direct comparisons between intentional multi-node attacks and random multi-node disruptions, alternative buffer allocation strategies, and parameter sensitivity analysis. Across these diverse simulation settings, the results demonstrated that the schedule risk network possesses an intrinsically heterogeneous structure, with inadequate supervision communication and implementation functioning as the core propagation hubs that drive systemic disruption across the broader network.
The simulation experiments further revealed that the 18 construction schedule risk factors fall into three distinct destructive levels, designated by the authors as systemic, conditional, and weak. While the coupled system proved resilient against random disruptions distributed across non-critical elements, it showed extreme fragility under targeted intervention. In intentional multi-node attack scenarios, removing or disabling just two central hub nodes was sufficient to trigger cascading failures that almost completely disabled the entire construction process network.
To counter these vulnerabilities, the researchers compared different schedule buffer management schemes, testing a risk-exposure-based weighted buffer allocation against conventional proportional allocation. The weighted allocation scheme delivered substantial performance gains, improving node functional robustness by 65.3 percent and collaborative efficiency by 127.5 percent relative to proportional allocation, despite introducing some compromise in schedule robustness. Consequently, the authors recommended a hybrid schedule management strategy using weighted allocation as the primary approach with minimum-threshold protection as supplementary support, providing methodological guidance for risk identification, buffer optimization, and robustness enhancement in pumped storage power station schedule management.
Subject of Research: Construction schedule risk networks and cascading failure robustness in pumped storage power stations
Article Title: Cascading failure and robustness enhancement mechanism of construction schedule risk-process coupling networks in pumped storage power stations
Article References: Ge, J., Hu, Z., Ding, S., Tian, K., Hao, D., & Fan, T. (2026). Cascading failure and robustness enhancement mechanism of construction schedule risk-process coupling networks in pumped storage power stations. Discover Applied Sciences. https://doi.org/10.1007/s42452-026-09834-0
Image Credits: AI Generated
DOI: 10.1007/s42452-026-09834-0
Keywords: pumped storage power stations, construction schedule risk, cascading failures, network robustness, Gray DEMATEL, buffer allocation, complex networks, project management, Cascading, failure, robustness, enhancement
News Source: Denise Maddox. (November 9, 2026). Two Hub Failures Can Cripple Pumped Storage Construction Schedules. Scienmag.
